{"id":"W7110048490","doi":"10.4230/lipics.cp.2025.17","title":"Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks","year":2025,"lang":"en","type":"article","venue":"DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National University of Singapore","keywords":"Trap (plumbing); Fixed point; Set (abstract data type); Probabilistic logic; Scalability; Enumeration; State space; Dynamical systems theory","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008558594,0.0002873546,0.0005048404,0.0003385797,0.0001867368,0.0003543472,0.0008266857,0.0001969598,0.000008066389],"category_scores_gemma":[0.0001398726,0.0002565832,0.0001287995,0.0005620694,0.0001497155,0.001197103,0.0004964019,0.0002981926,0.000009396153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006494963,"about_ca_system_score_gemma":0.00009339523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003712159,"about_ca_topic_score_gemma":0.0000958033,"domain_scores_codex":[0.9978663,0.00003987808,0.0009320144,0.0002746621,0.0002436689,0.0006434809],"domain_scores_gemma":[0.9986472,0.000239341,0.0003505646,0.0004697593,0.0001851975,0.0001079397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004282878,0.001246945,0.5921631,0.003712695,0.0004538159,0.00002230244,0.0468981,0.001073041,0.0001635356,0.2499946,0.0158883,0.08795526],"study_design_scores_gemma":[0.00596772,0.0003548777,0.04338917,0.0009675421,0.0000477899,0.00003057953,0.002189278,0.9186133,0.00133523,0.002889821,0.02346655,0.0007481719],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7308135,0.0005355867,0.2383729,0.000402094,0.001048707,0.001012104,0.00004676926,0.0001651576,0.02760319],"genre_scores_gemma":[0.9837314,0.00006486817,0.01521162,0.0004166353,0.0000491977,0.00003253771,0.00002906941,0.00001363172,0.0004510103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9175403,"threshold_uncertainty_score":0.9999886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009202968421726498,"score_gpt":0.2395445468036655,"score_spread":0.230341578381939,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}